WO2023097694A1

WO2023097694A1 - Decoding method, encoding method, decoder, and encoder

Info

Publication number: WO2023097694A1
Application number: PCT/CN2021/135529
Authority: WO
Inventors: 魏红莲
Original assignee: Oppo广东移动通信有限公司
Priority date: 2021-12-03
Filing date: 2021-12-03
Publication date: 2023-06-08

Abstract

Embodiments of the present application provide a decoding method, an encoding method, a decoder, and an encoder. The method comprises: sequentially decoding, from a code stream of a current point cloud, an attribute quantization residual value of a first component, an attribute quantization residual value of a second component, and an attribute quantization residual value of a third component of a current point, wherein the first component is a U component, a V component, a G component, or a B component; and obtaining an attribute reconstruction value of the current point on the basis of the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component. According to the present application, a first component to be decoded (i.e., the first component) of the current point is designed as a U component, a V component, a G component or a B component, so that the decompression performance can be improved.

Description

Decoding method, encoding method, decoder and encoder

technical field

The embodiments of the present application relate to the technical field of encoding and decoding, and more specifically, relate to a decoding method, an encoding method, a decoder, and an encoder.

Background technique

Point cloud has begun to be popularized in various fields, for example, virtual/augmented reality, robotics, geographic information system, medical field, etc. With the continuous improvement of the benchmark and speed of scanning equipment, a large number of point clouds on the surface of objects can be accurately obtained, often corresponding to hundreds of thousands of points in one scene. Such a large number of points also brings challenges to computer storage and transmission. Therefore, point-to-point compression and decompression has become a hot issue.

For point cloud compression, it is mainly necessary to compress its position information and attribute information. Specifically, the position information of the point cloud is firstly encoded by octree; at the same time, according to the position information of the current point encoded by the octree, the method used to predict the attribute prediction value of the current point is selected from the encoded points. After pointing, predict the attribute information of the current point based on the selected point, and then encode the attribute information by making a difference with the original value of the attribute information, so as to realize the encoding of the point cloud. For point cloud decompression, the process is the reverse process of point cloud compression.

So far, how to improve the decompression performance of the decoder is still a technical problem that needs to be solved urgently in this field.

Contents of the invention

Embodiments of the present application provide a decoding method, an encoding method, a decoder, and an encoder, which can improve decompression performance.

In a first aspect, the present application provides a decoding method, including:

Decode the attribute quantized residual value of the first component of the current point, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component from the code stream of the current point cloud in sequence; wherein, the first component is U component, V component, G component or B component;

Based on the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component, the attribute reconstruction value of the current point is acquired.

In a second aspect, the present application provides an encoding method, including:

Determine the attribute quantization residual value of the first component of the current point to be encoded in the current point cloud, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component; wherein, the first component is the U component , V component, G component or B component;

The attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component are sequentially encoded to obtain the code stream of the current point cloud.

In a third aspect, the present application provides a decoder, including:

The decoding unit is used to sequentially decode the attribute quantized residual value of the first component of the current point, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component from the code stream of the current point cloud; wherein, The first component is a U component, a V component, a G component or a B component;

An acquiring unit, configured to acquire the attribute reconstruction value of the current point based on the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component.

In a fourth aspect, the present application provides an encoder, including:

The determination unit is used to determine the attribute quantization residual value of the first component, the attribute quantization residual value of the second component and the attribute quantization residual value of the third component of the current point to be encoded in the current point cloud; wherein, the first One component is U component, V component, G component or B component;

The encoding unit is configured to sequentially encode the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component to obtain the code stream of the current point cloud.

In a fifth aspect, the present application provides a codec device, including:

a processor adapted to implement computer instructions; and,

A computer-readable storage medium, the computer-readable storage medium stores computer instructions, and the computer instructions are suitable for being loaded by a processor and executing any one of the above-mentioned first to second aspects or the encoding and decoding methods in each implementation manner.

In an implementation manner, there are one or more processors, and one or more memories.

In an implementation manner, the computer-readable storage medium may be integrated with the processor, or the computer-readable storage medium may be provided separately from the processor.

In a sixth aspect, the embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores computer instructions, and when the computer instructions are read and executed by a processor of a computer device, the computer device executes the above-mentioned first step. A codec method in any one of the first aspect to the second aspect or its various implementation manners.

Based on the above technical solutions, designing the first component to be decoded at the current point (that is, the first component) as a U component, a V component, a G component or a B component can improve decompression performance.

Description of drawings

Fig. 1 is an example of a point cloud image provided by an embodiment of the present application.

FIG. 2 is a partially enlarged view of the point cloud image shown in FIG. 1 .

Fig. 3 is an example of point cloud images with six viewing angles provided by the embodiment of the present application.

Fig. 4 is a schematic block diagram of a coding framework provided by an embodiment of the present application.

Fig. 5 is a schematic block diagram of a decoding framework provided by an embodiment of the present application.

Fig. 6 is an example of a bounding box provided by an embodiment of the present application.

FIG. 7 is an example of performing octree division on a bounding box provided by an embodiment of the present application.

8 to 10 show the encoding sequence of Morton codes in two-dimensional space.

Fig. 11 shows the encoding order of Morton codes in three-dimensional space.

Fig. 12 is a schematic flowchart of a decoding method provided by an embodiment of the present application.

Fig. 13 is a schematic flowchart of an encoding method provided by an embodiment of the present application.

Fig. 14 is a schematic block diagram of a decoder provided by an embodiment of the present application.

Fig. 15 is a schematic block diagram of an encoder provided by an embodiment of the present application.

Fig. 16 is a schematic block diagram of a codec device provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

A point cloud is a set of discrete point sets randomly distributed in space that express the spatial structure and surface properties of a 3D object or 3D scene. Figure 1 and Figure 2 show the 3D point cloud image and local enlarged view respectively, and it can be seen that the point cloud surface is composed of densely distributed points.

The two-dimensional image has information expression at each pixel, and the distribution is regular, so there is no need to additionally record its position information; however, the distribution of points in the point cloud in three-dimensional space is random and irregular, so it is necessary to record each The position of the point in space can completely express a point cloud. Similar to two-dimensional images, each position in the acquisition process has corresponding attribute information, usually RGB color value, and the color value reflects the color of the object; for point cloud, the attribute information corresponding to each point is in addition to color, Another common one is the reflectance value, which reflects the surface material of the object. Therefore, point cloud data usually includes geometric information (x, y, z) composed of three-dimensional position information, attribute information composed of three-dimensional color information (r, g, b), and one-dimensional reflectance information (r).

In other words, each point in the point cloud can include geometric information and attribute information, wherein the geometric information of each point in the point cloud refers to the Cartesian three-dimensional coordinate data of the point, and the attribute information of each point in the point cloud can include but It is not limited to at least one of the following: color information, material information, and laser reflection intensity information. The color information can be information on any color space. For example, the color information may be Red Green Blue (RGB) information. For another example, the color information may also be brightness and chrominance (YCbCr, YUV) information. Among them, Y represents brightness (Luma), Cb (U) represents a blue chroma component, and Cr (V) represents a red chroma component. Each point in the point cloud has the same amount of attribute information. For example, each point in the point cloud has two attribute information, color information and laser reflection intensity. For another example, each point in the point cloud has three attribute information: color information, material information and laser reflection intensity information.

The point cloud image can have multiple viewing angles, for example, the point cloud image shown in Figure 3 can have six viewing angles, the data storage format corresponding to the point cloud image consists of a file header information part and a data part, the header information It includes the data format, data representation type, total point cloud points, and the content represented by the point cloud.

As an example, the data storage format of a point cloud image can be implemented as the following format:

ply

format ascii 1.0

element vertex 207242

property float x

property float y

property float z

property uchar red

property uchar green

property uchar blue

75 318 0 0 142 0

75 319 0 0 143 0

75 319 1 1 9 9

75 315 0 1 9 9

For the data storage format of the above point cloud image, the data format is ".ply" format, represented by ASCII code, the total number of points is 207242, and each point has three-dimensional position information xyz and three-dimensional color information rgb.

Point cloud can flexibly and conveniently express the spatial structure and surface properties of three-dimensional objects or scenes, and because point cloud is obtained by directly sampling real objects, it can provide a strong sense of reality under the premise of ensuring accuracy, so it is widely used. Including virtual reality games, computer-aided design, geographic information systems, automatic navigation systems, digital cultural heritage, free viewpoint broadcasting, 3D immersive telepresence, 3D reconstruction of biological tissues and organs, etc.

Based on application scenarios, point clouds can be divided into two categories, namely, machine-perceived point clouds and human-eye-perceived point clouds. The application scenarios of machine perception point cloud include but are not limited to: autonomous navigation system, real-time inspection system, geographic information system, visual sorting robot, emergency rescue robot and other point cloud application scenarios. The application scenarios of point cloud perceived by the human eye include but are not limited to: digital cultural heritage, free viewpoint broadcasting, 3D immersive communication, 3D immersive interaction and other point cloud application scenarios. Correspondingly, the point cloud can be divided into dense point cloud and sparse point cloud based on the acquisition method of the point cloud; the point cloud can also be divided into static point cloud and dynamic point cloud based on the acquisition method of the point cloud, more specifically, it can be It is divided into three types of point clouds, namely, the first static point cloud, the second type of dynamic point cloud and the third type of dynamically acquired point cloud. For the first static point cloud, the object is stationary, and the device for obtaining the point cloud is also stationary; for the second type of dynamic point cloud, the object is moving, but the device for obtaining the point cloud is stationary; for the third type of dynamic Obtaining point cloud, the equipment for obtaining point cloud is in motion.

The collection of point clouds mainly has the following methods: computer generation, 3D laser scanning, 3D photogrammetry, etc. Computers can generate point clouds of virtual three-dimensional objects and scenes; 3D laser scanning can obtain point clouds of static real-world three-dimensional objects or scenes, and can obtain millions of point clouds per second; 3D photogrammetry can obtain dynamic real-world three-dimensional objects or scenes The point cloud of tens of millions of points can be obtained per second. Specifically, the point cloud of the surface of the object can be collected through acquisition equipment such as photoelectric radar, lidar, laser scanner, and multi-view camera. The point cloud obtained according to the laser measurement principle may include the three-dimensional coordinate information of the point and the laser reflection intensity (reflectance) of the point. The point cloud obtained according to the principle of photogrammetry may include the three-dimensional coordinate information of the point and the color information of the point. The point cloud is obtained by combining the principles of laser measurement and photogrammetry, which may include the three-dimensional coordinate information of the point, the laser reflection intensity (reflectance) of the point and the color information of the point. These technologies reduce the cost and time period of point cloud data acquisition, and improve the accuracy of the data. For example, in the medical field, point clouds of biological tissues and organs can be obtained from magnetic resonance imaging (MRI), computed tomography (CT), and electromagnetic positioning information. These technologies reduce the acquisition cost and time period of point cloud, and improve the accuracy of data. The transformation of the point cloud data acquisition method has made it possible to acquire a large amount of point cloud data. With the growth of application requirements, the processing of massive 3D point cloud data encounters the bottleneck of storage space and transmission bandwidth limitations.

Taking a point cloud video with a frame rate of 30fps (frame per second) as an example, the number of points in each frame of point cloud is 700,000, and each point in each frame of point cloud has coordinate information xyz (float) and color information RGB ( uchar), the data volume of 10s point cloud video is about 0.7million·(4Byte·3+1Byte·3)·30fps·10s=3.15GB, while the YUV sampling format is 4:2:0, and the frame rate is 1280 at 24fps For ×720 two-dimensional video, the data volume of 10s is about 1280·720·12bit·24frames·10s≈0.33GB, and the data volume of 10s of two-view 3D video is about 0.33·2=0.66GB. It can be seen that the data volume of point cloud video far exceeds the data volume of 2D video and 3D video of the same duration. Therefore, in order to better realize data management, save server storage space, and reduce the transmission traffic and transmission time between the server and the client, point cloud compression has become a key issue to promote the development of the point cloud industry.

Point cloud compression generally uses point cloud geometric information and attribute information to compress separately. Compression of cloud attributes; at the decoding end, the geometric information of the point cloud is first decoded in the geometric decoder, and then the decoded geometric information is input into the attribute decoder as additional information to assist in the compression of the point cloud attributes. The entire codec consists of preprocessing/postprocessing, geometric encoding/decoding, and attribute encoding/decoding.

Point clouds can be encoded and decoded by various types of encoding frameworks and decoding frameworks, respectively. As an example, the codec framework may be the Geometry Point Cloud Compression (G-PCC) codec framework or Video Point Cloud Compression (Video Point Cloud Compression) provided by the Moving Picture Experts Group (MPEG). , V-PCC) codec framework, or the AVS-PCC codec framework or Point Cloud Compression Reference Platform (PCRM) framework provided by the Audio Video Standard (AVS) task force. The G-PCC codec framework can be used to compress the first static point cloud and the third type of dynamically acquired point cloud, and the V-PCC codec framework can be used to compress the second type of dynamic point cloud. The G-PCC codec framework is also called point cloud codec TMC13, and the V-PCC codec framework is also called point cloud codec TMC2. Both G-PCC and AVS-PCC are aimed at static sparse point clouds, and their coding frameworks are roughly the same. The codec framework applicable to the embodiment of the present application will be described below by taking the PCRM framework as an example.

As shown in Figure 4, in the encoding framework, the geometric information of point cloud and the attribute information corresponding to each point are encoded separately.

In the geometric coding part of the encoding end, firstly, the original geometric information is preprocessed, that is, the geometric origin is normalized to the minimum value position in the point cloud space through coordinate translation, and the geometric information is converted from floating point numbers to integers through coordinate quantization , which is convenient for subsequent regularization processing. Since the geometric information of some points is the same due to quantization and rounding, it is necessary to decide whether to remove duplicate points at this time. Quantization and removal of duplicate points belong to the preprocessing process; then, the regularized geometric information is Geometric coding, that is, to use the octree structure to recursively divide the point cloud space. Each time the current block is divided into eight sub-blocks of the same size, and the occupancy of each sub-block is judged. When the sub-block does not contain points When it is recorded as empty, otherwise it is recorded as non-empty. In the last layer of recursive division, the occupied codeword information of all blocks is recorded and encoded; the geometric information expressed by the octree structure is input to the geometric entropy encoder on the one hand to form Geometry stream.

In addition, after the geometric encoding is completed, the geometric information is reconstructed, and the attribute information is encoded by using the reconstructed geometric information.

In the attribute coding part, firstly, the attribute coding is mainly for the coding of color and reflectance information. First, determine whether to perform color space conversion. If the processed attribute information is color information, the original color needs to be transformed into a YUV color space that is more in line with the visual characteristics of the human eye; then, the geometric lossy In the case of encoding, since the geometric information changes after geometric encoding, it is necessary to reassign attribute values for each point after geometric encoding, so that the attribute error between the reconstructed point cloud and the original point cloud is minimized. This process is called attribute interpolation or Attribute recoloring; then, attribute encoding is performed on the preprocessed attribute information, which is divided into attribute prediction and attribute transformation; the attribute prediction process refers to the reordering of point clouds and attribute prediction. The reordering methods include Morton reordering and Hilbert (Hilbert) reordering; for example, the Hilbert code is used in the AVS coding framework to reorder the point cloud; the sorted point cloud uses a differential method for attribute prediction , specifically, if the geometric information of the current point to be encoded is the same as that of the previous encoded point, that is, it is a repeated point, then use the reconstructed attribute value of the repeated point as the attribute prediction value of the current point to be encoded, otherwise select The m points of the previous Hilbert order are used as neighbor candidate points, and then the Manhattan distance between them and the geometric information of the current point to be encoded is calculated respectively, and the n points with the closest distance are determined as the prediction points of the current point to be encoded, and the distance The reciprocal is used as the weight, and the weighted average of the attributes of n neighbors is calculated as the attribute prediction value of the current point to be encoded.

For example, the attribute prediction value of the current point to be encoded can be obtained in the following ways:

PredR=(1/W ₁ ×ref ₁ +1/W ₂ ×ref ₂ +1/W ₃ ×ref ₃ )/(1/W ₁ +1/W ₂ +1/W ₃ ).

Among them, W ₁ , W ₂ , W ₃ represent the geometric distances between predicted point 1, predicted point 2, predicted point 3 and the current point to be coded, ref ₁ , ref ₂ , ref ₃ represent predicted point 1, predicted point 2, Predict the attribute reconstruction value for point 3.

After the attribute prediction value of the current point to be encoded is obtained, the residual value of the current point to be encoded is obtained based on the attribute prediction value of the current point to be encoded, and the residual value is the difference between the original attribute value and the predicted attribute value of the current point to be encoded value; finally, the residual value is quantized, and the quantized residual is input into the attribute entropy encoder to form an attribute code stream.

As shown in Figure 5, at the decoding end, the geometry and attributes are also decoded separately. In the geometric decoding part, the geometric code stream is first entropy decoded to obtain the geometric information of each point, and then the octree structure is constructed in the same way as the geometric encoding, and the coordinate transformation is reconstructed by combining the decoded geometry. The geometric information expressed by the structure, on the one hand, coordinate inverse quantization and inverse translation of the information to obtain the decoded geometric information, on the other hand, it is input into the attribute decoder as additional information. In the attribute decoding part, the Morton order is constructed in the same way as the encoding side, and the attribute code stream is entropy decoded to obtain the quantized residual information; then inverse quantization is performed to obtain the point cloud residual; similarly, according to the In the same manner as attribute encoding, the attribute prediction value of the current point to be decoded is obtained, and then the attribute prediction value is added to the residual value to restore the YUV attribute value of the current point to be decoded; finally, the decoded attribute is obtained through inverse color space transformation information.

For the convenience of description, the regularization processing method of point cloud is described below.

Due to the irregular distribution of point cloud in space, it brings challenges to the encoding process, so the recursive octree structure is adopted, as shown in Figure 6, to express the points in the point cloud as the center of the cube in a regular way. Specifically, the entire point cloud is first placed in a cube bounding box, and the coordinates of the point cloud midpoint are expressed as (x ^k , y ^k , z ^k ), k=0,...,K-1, where K is The total number of points in the point cloud, and the boundary values of the point cloud in the x, y, and z directions are:

x ^min =min(x ⁰ ,x ¹ ,…,x ^K-1 );

y ^min =min(y ⁰ ,y ¹ ,...,y ^K-1 );

z ^min =min(z ⁰ ,z ¹ ,...,z ^K-1 );

x ^max = max(x ⁰ ,x ¹ ,...,x ^K-1 );

y ^max = max(y ⁰ ,y ¹ ,...,y ^K-1 );

z ^max = max(z ⁰ , z ¹ , . . . , z ^K−1 ).

Then the origin (x ^origin , y ^origin , z ^origin ) of the bounding box can be calculated as follows:

x ^origin = int(floor(x ^min ));

y ^origin = int(floor(y ^min ));

z ^origin = int(floor(z ^min )).

Among them, floor() represents the calculation of rounding down or rounding down. int() means rounding operation.

Based on the calculation formula of the boundary value and the origin, the size of the bounding box in the x, y, and z directions can be calculated as follows:

BoudingBoxSize_x=int(x ^max -x ^origin )+1;

BoudingBoxSize_y=int(y ^max -y ^origin )+1;

BoudingBoxSize_z=int(z ^max -z ^origin )+1.

As shown in Figure 7, after obtaining the dimensions of the bounding box in the x, y, and z directions, the bounding box is first divided into octrees, and eight sub-blocks are obtained each time, and then the non-empty blocks in the sub-blocks (including points) block) to divide the octree again, so recursively divide until a certain depth, the non-empty sub-block of the final size is called a voxel (voxel), each voxel contains one or more points, and the points of these points The geometric position is normalized to the center point of the voxel, and the attribute value of the center point is the average value of the attribute values of all points in the voxel. Regularizing the point cloud into blocks in space is conducive to the description of the relationship between points and points in the point cloud, and then can express a specific encoding order, and determine a certain order to encode each voxel (voxel), that is, the encoded voxel represents Point (or "node"), a commonly used encoding order is the cross-separated Morton order.

8 to 10 show the encoding sequence of Morton codes in two-dimensional space. Fig. 11 shows the encoding order of Morton codes in three-dimensional space. The order of the arrows indicates the encoding order of the points under the Morton order. Figure 8 shows the "z"-shaped Morton coding sequence of 2*2 pixels in two-dimensional space, and Figure 9 shows the "z"-shaped Morton coding sequence between four 2*2 blocks in two-dimensional space , FIG. 10 shows the Morton coding order of the "z" shape between four 4*4 blocks in a two-dimensional space, which constitutes the Morton coding order of the entire 8*8 block. The Morton coding sequence extended to three-dimensional space is shown in Figure 11. Figure 11 shows 16 points, and the Morton coding sequence between each "z" and "z" inside each "z" is It is encoded along the x-axis first, then along the y-axis, and finally along the z-axis.

The attribute intra-frame prediction part in point cloud compression, for the color attribute, mainly refers to the adjacent points of the current point to predict the current point. The difference information is transmitted to the decoding end; after the decoding end receives and analyzes the code stream, it obtains the residual information through steps such as inverse transformation and inverse quantization, and the decoding end predicts and obtains the attribute prediction value through the same process, and obtains the current point after superimposing it with the residual information Property reconstruction value.

Exemplarily, for different test conditions, different color information formats are used.

Under the C1 test condition and under the C2 test condition, the color attributes of the input point cloud can be converted from RGB to YUV space. The C1 test conditions may refer to test conditions for limit-lossy geometry compression and lossy attributes compression. The C2 test conditions may refer to test conditions for geometric lossless compression and lossy attributes compression.

Exemplarily, the conversion formula for converting the color attribute of the input point cloud from RGB space to YUV space may be as follows:

Y＝0.2126*R+0.7152*G+0.0722*B;

U＝-0.114572*R-0.385428*G+0.5*B+128;

V＝0.5*R-0.454153*G-0.045847*B+128;

Exemplarily, the inverse transformation formula for converting the color attribute of the input point cloud from YUV space to RGB space can be as follows:

R=Y+1.5748*(V-128);

G=Y–0.18733*(U-128)–0.46813*(V-128);

B=Y+1.85563*(U-128);

Under the C3 test condition and C4 test condition, the point cloud in RGB format can be directly used as the input point cloud. The C3 test conditions may refer to test conditions for geometrically lossless compression and limit-lossy attributes compression. C4 test conditions may refer to test conditions for geometric lossless compression and attribute lossless compression. C3 test conditions and C4 test conditions avoid errors in attribute information caused by color space conversion, and can improve compression performance.

The attribute information of the processed point cloud will be input into the point cloud attribute compression encoder in the order of YUV (or RGB), and each point will be predicted, quantized, and entropy encoded in sequence according to the index order of the points in the point cloud. To facilitate the understanding of the solution of the present application, the encoding process of the encoder is described as an example below. The specific encoding steps are described as follows:

a) Find N predicted points for the current point within the range formed by the encoded points between the current points.

b), respectively calculate the weight value of each prediction point in the N prediction points according to the geometric distance between the N prediction points and the current point, and reconstruct the value according to the weight value of each prediction point and the attribute of each point ( Including the attribute reconstruction value of Y component, U component and V component or the attribute reconstruction value of R component, G component and B component), calculate the attribute prediction value of the current point (including the attribute prediction value of Y component, U component and V component or attribute prediction values of the R component, the G component, and the B component).

For example, if the format of the attribute information of the current point is YUV format, the encoder can calculate the attribute prediction value of the Y component of the current point according to the weight value of each prediction point and the Y component of each prediction point, and according to each prediction Calculate the attribute prediction value of the U component of the current point based on the weight value of the point and the U component of each prediction point, and calculate the attribute prediction of the V component of the current point according to the weight value of each prediction point and the V component of each prediction point value. For another example, if the attribute information format of the current point is in RGB format, the encoder can calculate the attribute prediction value of the R component of the current point according to the weight value of each prediction point and the attribute reconstruction value of the R component of each prediction point , according to the weight value of each prediction point and the attribute reconstruction value of the G component of each prediction point, calculate the attribute prediction value of the G component of the current point, according to the weight value of each prediction point and the B component of each prediction point Attribute reconstruction value, calculate the attribute prediction value of the B component of the current point.

Exemplarily, the attribute prediction value of each component can be determined by the following formula:

Among them, A ^p represents the attribute prediction value of each component, w _i represents the weight value of the i-th prediction point among the N prediction points, and A _i represents the attribute prediction value of each component of the i-th point among the N prediction points . For example, if the format of the color information of the current point is YUV format, then each component can include Y component, U component and V component; if the format of the color information of the current point is RGB format, then each component can include R component, G component and the B component.

c) The encoder calculates the attribute residual value of each component according to the attribute prediction value of each component and the cross-component prediction value of each component.

For example, if the color attribute of the current point is in the YUV space, the attribute residual value of each component of the current point can be calculated sequentially in the order of Y component, U component, and V component; if the color attribute of the current point is in the RGB space, then you can The attribute residual value of each component of the current point is calculated sequentially in the order of R component, G component, and B component.

Exemplarily, the attribute residual value of each component can be calculated according to the following formula:

delta = currValue-predictor-residualPrevComponent;

Among them, delta represents the attribute residual value of each component, currValue represents the original value or real value of each component, predictor represents the attribute prediction value of each component, and residualPrevComponent represents the cross-component prediction value of each component. For example, if the format of the color information of the current point is YUV format, then each component can include Y component, U component and V component; if the format of the color information of the current point is RGB format, then each component can include R component, G component and the B component.

Exemplarily, for the Y component and the R component, since they are the first encoded components, the cross-component prediction value of the Y component and the R component can be set to 0, and for the U component, V component, G component, and B component, its The cross-component prediction value is determined according to the reconstruction value of the attribute residual obtained by inverse quantization of the attribute quantization residual value of the previously encoded component. For example, the cross-component prediction value of the U component can be the attribute residual reconstruction value obtained by inverse quantization of the attribute quantization residual value of the Y component, and the cross-component prediction value of the G component can be the attribute quantization residual value of the R component. The reconstructed value of the attribute residual obtained by inverse quantization. For another example, the cross-component prediction value of the V component may be the attribute residual reconstruction value obtained by dequantizing the attribute quantization residual value of the Y component and the attribute residual reconstruction value obtained by dequantizing the attribute quantization residual value of the U component. The sum of values, the cross-component prediction value of the B component can be the attribute residual reconstruction value obtained by dequantizing the attribute quantized residual value of the R component and the attribute residual obtained by dequantizing the attribute quantized residual value of the G component Sum of reconstructed values.

After the encoder obtains the attribute residual value of each component, it performs a quantization operation on the attribute residual value of each component to obtain the attribute quantized residual value of each component of the current point. For example, if the format of the color information of the current point is YUV format, the attribute residual value of each component of the current point is sequentially quantized in the order of Y component, U component, and V component to obtain the attribute quantized residual value of each component. For another example, if the format of the color information of the current point is RGB format, the attribute residual value of each component of the current point is sequentially quantized in the order of R component, G component, and B component to obtain the attribute quantized residual value of each component.

d) The encoder performs entropy encoding on the attribute quantization residual value of each component of the current point to obtain the code stream of the point cloud.

For example, if the format of the color information of the current point is YUV format, entropy encoding is performed on the attribute quantization residual value of each component in the order of Y component, U component, and V component to obtain the code stream of the point cloud. For another example, if the format of the color information of the current point is RGB format, entropy encoding is performed on the attribute quantization residual value of each component in the order of R component, G component, and B component to obtain the code stream of the point cloud.

Exemplarily, the entropy coding may be performed on the attribute quantization residual value of each component of the current point according to the following steps:

1) On the one hand, introduce a flag bit flag_r, for points whose attribute information format is YUV format, it can be used to indicate whether the attribute quantization residual value of the Y component is 0, for points whose attribute information format is RGB format, It can be used to indicate whether the attribute quantization residual value of the R component is 0. For example, if the attribute quantization residual value of the Y component (or R component) is 0, then flagy_r=0, otherwise flagy_r=1, the encoder encodes the value of flag_r and writes it into the code stream. On the other hand, another flag flagyu_rg is introduced, which can be used to indicate whether the attribute residual quantization value of the Y component and the attribute residual quantization value of the U component are both 0 for points whose attribute information format is YUV format. The format of the information is a point in RGB format, which can be used to indicate whether the attribute residual quantization value of the R component and the attribute residual quantization value of the G component are both 0. For example, if both the attribute residual quantization value of the Y component and the attribute residual quantization value of the U component are 0, then flagyu_rg=0, otherwise flagyu_rg=1. For another example, if both the attribute residual quantization value of the R component and the attribute residual quantization value of the G component are 0, then flagyu_rg=0, otherwise flagyu_rg=1.

2) The encoder judges whether the attribute quantization residual value of the Y component (or R component) is 0, and if it is 0, executes the following 3), otherwise executes the following 4).

3), the encoder encodes the value of flagyu_rg, and judges whether the attribute quantization residual value of the U component (or G component) is 0, if the attribute quantization residual value of the U component (or G component) is 0, then The attribute quantized residual value of the V component (or B component) is encoded, otherwise, the attribute residual quantized values of the U component and the V component (or the G component and the B component) are encoded sequentially.

For example, if the format of the color information of the current point is YUV format, the encoder encodes the value of flagyu_rg, and judges whether the attribute quantization residual value of the U component is 0, if the attribute quantization residual value of the U component is 0 , then encode the attribute quantized residual value of the V component, otherwise encode the attribute residual quantized value of the U component and the attribute residual quantized value of the V component in sequence. For another example, if the color information format of the current point is in RGB format, the encoder encodes the value of flagyu_rg and judges whether the attribute quantization residual value of the G component is 0. If the attribute quantization residual value of the G component is 0, the attribute quantization residual value of the B component is encoded, otherwise, the attribute residual quantization value of the G component and the attribute residual quantization value of the B component are encoded sequentially.

4) The encoder sequentially encodes the attribute quantized residual values of the Y component, U component, and V component (or R component, G component, and B component).

For example, if the format of the color information of the current point is YUV format, the encoder encodes the attribute quantization residual value of the Y component, the attribute quantization residual value of the U component, and the attribute quantization residual value of the V component in sequence. For another example, if the format of the color information of the current point is the RGB format, the encoder sequentially encodes the attribute quantization residual value of the R component, the attribute quantization residual value of the G component, and the attribute quantization residual value of the B component.

e) For the attribute quantization residual value of each component, the encoder performs inverse quantization in the order of Y component, U component, V component (or R component, G component, B component), and then adds the attribute prediction value of the corresponding component and cross-component prediction values to generate attribute reconstruction values for the corresponding components of the current point.

For example, if the format of the color information of the current point is YUV format, then for the attribute quantization residual value of each component, the encoder performs inverse quantization in the order of Y component, U component, and V component, and then adds the attribute prediction of the corresponding component Values and cross-component predictions to generate attribute reconstruction values for the corresponding components of the current point. For another example, if the format of the color information of the current point is RGB format, then for the attribute quantization residual value of each component, the encoder performs inverse quantization in the order of R component, G component, and B component, and then adds the attribute of the corresponding component Predicted value and cross-component predicted value, generate the attribute reconstruction value of the corresponding component of the current point.

Exemplarily, the attribute reconstruction value of each component of the current point can be generated according to the following formula:

in,

Indicates the attribute reconstruction value of each component of the current point,

Indicates the attribute residual reconstruction value after inverse quantization of each component, predictor indicates the attribute prediction value of each component, and residualPrevComponent indicates the cross-component prediction value of each component. For example, if the format of the color information of the current point is YUV format, then each component can include Y component, U component and V component; if the format of the color information of the current point is RGB format, then each component can include R component, G component and the B component.

It should be understood that in step c), the attribute quantization residual value of each component will be dequantized to obtain the attribute residual reconstruction value of each component. Therefore, the generation process of the attribute reconstruction value of each component in step e) can also be integrated in step c). In addition, if the generation process of the attribute reconstruction value of each component in step e) is integrated in step c), then the generation process of the attribute reconstruction value of each component can also follow the U component, Y component, V component (or G component, G component, The order of R component, B component) is dequantized. This application does not specifically limit it.

Correspondingly, the specific execution steps of the decoding end are described as follows:

a), find N predicted points for the current point within the range formed by the points that have been decoded between the current points;

b), respectively calculate the weight value of each prediction point in the N prediction points according to the geometric distance between the N prediction points and the current point, and reconstruct the value according to the weight value of each prediction point and each attribute (including The attribute reconstruction value of Y component, U component and V component or the attribute reconstruction value of R component, G component and B component), calculate the attribute prediction value of the current point (including the attribute prediction value of Y component, U component and V component or R component, G component, and attribute prediction value of B component).

c) According to the order of Y component, U component, V component (or R component, G component, B component), decode from the code stream to obtain the attribute quantization residual value of each component at the current point.

For example, if the format of the color information of the current point is YUV format, the decoder decodes the attribute quantization residual value of each component of the current point from the code stream in the order of Y component, U component, and V component. For another example, if the format of the color information of the current point is RGB format, the encoder decodes the attribute quantization residual value of each component of the current point from the code stream in the order of R component, G component, and B component.

Exemplarily, the specific execution steps include:

1) Obtain the flag bit flag_r by decoding from the code stream. If flag_r is 0, the attribute quantization residual value of the Y component (or R component) is 0. If flag_r is 1, the attribute of the Y component (or R component) The quantized residual value is not 0.

For example, if the format of the color information of the current point is YUV format, the decoder decodes and obtains the flag bit flag_r from the code stream. If flag_r is 0, the attribute quantization residual value of the Y component is 0, and flag_r is 1, then Y The attribute quantization residual value of the component is not 0. For another example, if the color information format of the current point is in RGB format, the decoder decodes and obtains the flag bit flag_r from the code stream. If flag_r is 0, the attribute quantization residual value of the R component is 0. If flag_r is 1, Then the attribute quantization residual value of the R component is not 0.

2) Judging whether the attribute quantization residual value of the Y component (or R component) is 0, if it is 0, perform 3), otherwise perform 4).

3) Obtain the flag bit flagyu_rg by decoding from the code stream. If flagyu_rg is 0, the attribute quantization residual value of the U component (or G component) is 0, and decode and obtain the value of the V component (or B component) from the code stream Attribute quantized residual value; otherwise, decode and obtain the attribute quantized residual value of U component, V component (or G component, B component) from the code stream in sequence.

For example, if the format of the color information of the current point is YUV format, the decoder decodes and obtains the flag bit flagyu_rg from the code stream. If flagyu_rg is 0, the attribute quantization residual value of the U component is 0, and decodes it from the code stream Obtain the attribute quantization residual value of the V component; otherwise, sequentially decode and obtain the attribute quantization residual value of the U component and the attribute quantization residual value of the V component from the code stream. For another example, if the color information format of the current point is in RGB format, the decoder decodes the flag bit flagyu_rg from the code stream. If flagyu_rg is 0, the attribute quantization residual value of the G component is 0, and the Decode to obtain the attribute quantization residual value of the B component; otherwise, decode and obtain the attribute quantization residual value of the G component and the attribute quantization residual value of the B component from the code stream in sequence.

4) Decoding and obtaining attribute quantization residual values of the Y component, U component, and V component (or R component, G component, and B component) from the code stream in sequence.

For example, if the format of the color information of the current point is YUV format, the decoder decodes and obtains the flag bit flag_r from the code stream, and if flag_r is 1, the decoder sequentially decodes and obtains the attribute quantization residual value of the Y component from the code stream , the attribute quantized residual value of the U component and the attribute quantized residual value of the V component. For another example, if the format of the color information of the current point is in RGB format, the decoder decodes from the code stream to obtain the flag bit flag_r, if flag_r is 1, the decoder sequentially decodes from the code stream to obtain the attribute quantization residual of the R component value, the attribute quantized residual value of the G component, and the attribute quantized residual value of the B component.

d) For the attribute quantization residual value of each component, the encoder performs inverse quantization in the order of Y component, U component, V component (or R component, G component, B component), and then adds the attribute prediction value of the corresponding component and cross-component prediction values to generate attribute reconstruction values for the corresponding components of the current point.

in,

In the above scheme, if the format of the color information of the current point is YUV format, the encoder encodes the attribute quantization residual value of each component of the current point in the order of Y component, U component, and V component. If the color information of the current point The format of the information is RGB format, and the encoder encodes the attribute quantization residual value of each component in the order of R component, G component, and B component; correspondingly, if the format of the color information of the current point is YUV format, the decoder follows The sequence of Y component, U component, and V component decodes the attribute quantization residual value of each component of the current point. If the format of the color information of the current point is RGB format, the decoder follows the sequence of R component, G component, and B component The attribute quantized residual values of the respective components are decoded.

It should be noted that, in the above scheme, the decoder needs to decode two flag bits when decoding the attribute quantization residual value of each component of the current point. On the one hand, a flag bit flag_r is introduced, and the format for the attribute information is YUV Format point, which can be used to indicate whether the attribute quantization residual value of the Y component is 0, and for a point whose attribute information format is RGB format, it can be used to indicate whether the attribute quantization residual value of the R component is 0. For example, if the attribute quantization residual value of the Y component (or R component) is 0, then flagy_r=0, otherwise flagy_r=1, the encoder encodes the value of flag_r and writes it into the code stream. On the other hand, another flag flagyu_rg is introduced, which can be used to indicate whether the attribute residual quantization value of the Y component and the attribute residual quantization value of the U component are both 0 for points whose attribute information format is YUV format. The format of the information is a point in RGB format, which can be used to indicate whether the attribute residual quantization value of the R component and the attribute residual quantization value of the G component are both 0. For example, if both the attribute residual quantization value of the Y component and the attribute residual quantization value of the U component are 0, then flagyu_rg=0, otherwise flagyu_rg=1. For another example, if both the attribute residual quantization value of the R component and the attribute residual quantization value of the G component are 0, then flagyu_rg=0, otherwise flagyu_rg=1.

In the specific decoding process, it is judged whether the attribute quantization residual value of the Y component (or R component) is 0, if it is 0, perform 3), otherwise perform 4). That is to say, when flag_r is 0, no matter whether flagyu_rg is 0 or not, the decoder needs to decode flag_r and flagyu_rg. When flagy_r is not 0, the decoder does not need to decode flagyu_rg. In other words, from the perspective of big data statistics, based on the possibility that each component is not 0, it may affect whether flagy_r is 0, which in turn will affect whether the decoding end needs to decode flagyu_rg, and will eventually affect the decoder. decoding efficiency.

In view of this, the present application provides a decoding method, which improves decoding efficiency by changing the decoding order of components before this point.

Fig. 12 is a schematic flowchart of a decoding method 100 provided by an embodiment of the present application. The method 100 can be executed by a decoder or a decoding framework, such as the decoding framework shown in FIG. 5 .

As shown in Figure 12, the decoding method 100 may include:

S110, sequentially decode the attribute quantization residual value of the first component of the current point, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component from the code stream of the current point cloud; wherein, the first The component is U component, V component, G component or B component;

S120. Acquire an attribute reconstruction value of the current point based on the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component.

In this embodiment, the first component to be decoded (that is, the first component) at the current point is designed as a U component, a V component, a G component or a B component, which can improve decompression performance.

In addition, the first component to be decoded at the current point (that is, the first component) is designed as a U component or a V component. Considering that the luminance component contains more visual information, this application first decodes the U component or the V component Decoding the Y component is equivalent to determining the cross-component prediction value of the Y component based on the attribute residual reconstruction value of the U component or the attribute residual reconstruction value of the V component, and then determining the Y component based on the cross-component prediction value of the Y component When the attribute reconstruction value of , the accuracy of the attribute reconstruction value of the Y component can be improved, thereby improving the decompression performance.

The applicant tested the solution provided by this application on the point cloud compression platform, and the test results are shown in Table 1 to Table 4.

Table 1 is the BD-rate of each component of Cat1B, Cat1C and Cat3 in the case of limit-lossy geometry compression and lossy attributes compression. Cat1B, Cat1C and Cat3 represent different types of Point cloud of attribute information. Table 2 is the BD-rate of each component of Cat1B, Cat1C and Cat3 in the case of lossless geometry compression and attribute lossy compression. Table 3 is the BD-rate of each component of Cat1B, Cat1C and Cat3 in the case of geometric lossless compression and limit-lossy attributes compression. Table 4 shows the bpip ratios of Cat1B, Cat1C and Cat3 in the case of geometric lossless compression and attribute lossless compression.

Table 1

Table 2

table 3

Table 4

测试序列test sequence	bpip比率(bpip ratio)bpip ratio (bpip ratio)
Cat1BCat1B	99.9％99.9%
Cat1CCat1C	100.0％100.0%
Cat3Cat3	99.4％99.4%

As shown in Table 1 to Table 3, "-" represents the decrease in rate distortion (Bit distortion, BD-rate), and BD-rate represents the bit rate difference under the same peak signal-to-noise ratio (Peak Signal to Noise Ratio, PSNR), BD The smaller the -rate, the better the performance of the encoding algorithm. As shown in FIG. 4 , the larger the value of the bpip ratio, the better the performance of the encoding algorithm. It can be seen from Table 1 to Table 4 that the decoding method provided by the present application has obvious performance improvement.

Of course, the present application does not limit the specific implementation manners of the second component and the third component.

For example, the first component is a U component, the second component may be a V component, and the third component may be a Y component.

For another example, the first component is a U component, the second component may be a Y component, and the third component may be a V component.

For another example, the first component is a V component, the second component may be a Y component, and the third component may be a U component.

For another example, the first component is a V component, the second component may be a U component, and the third component may be a Y component.

For another example, the first component is a G component, the second component may be an R component, and the third component may be a B component.

For another example, the first component is a G component, the second component may be a B component, and the third component may be an R component.

For another example, the first component is a B component, the second component may be an R component, and the third component may be a G component.

For another example, the first component is a B component, the second component may be a G component, and the third component may be an R component.

In some embodiments, the S110 may include:

Decoding the code stream to obtain a first identifier, the value of the first identifier is used to indicate whether the attribute quantization residual value of the first component is zero;

The code stream is analyzed based on the value of the first identifier, and the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component are obtained.

For example, if the format of the attribute information of the current point is YUV format, assuming that the first component is a U component, the second component can be a Y component, and the third component can be a V component, then the decoder decodes the code stream , to obtain the first identification, the value of the first identification is used to indicate whether the attribute quantization residual value of the U component is zero; after the decoder obtains the first identification, it can base the value of the first identification on the code stream Perform analysis to obtain the attribute quantization residual value of the U component, the attribute quantization residual value of the Y component, and the attribute quantization residual value of the V component in sequence. For another example, if the format of the attribute information of the current point is RGB format, assuming that the first component is the G component, the second component can be the R component, and the third component can be the B component, then the decoder performs Decoding to obtain the first identification, the value of the first identification is used to indicate whether the attribute quantization residual value of the G component is zero; after the decoder obtains the first identification, it can base the value of the first identification on the code The stream is analyzed to obtain the attribute quantization residual value of the G component, the attribute quantization residual value of the R component, and the attribute quantization residual value of the V component in sequence.

In some embodiments, if the value of the first identifier is the first value, the decoder determines that the attribute quantization residual value of the first component is zero, and based on the second identifier obtained by decoding the code stream, Obtain the attribute residual value of the second component and the attribute residual value of the third component; the value of the second identifier is used to represent the attribute quantized residual value of the first component and the attribute quantized residual value of the second component Whether the differences are all zero. For example, the first value may be 0 or other values.

For example, taking the attribute information format of the current point as an example in YUV format, assuming that the first component is a U component, the second component may be a Y component, and the third component may be a V component. value is the first value, the decoder determines that the attribute quantization residual value of the U component is zero, and based on the second identifier obtained by decoding the code stream, obtains the attribute residual value of the Y component and the attribute residual value of the V component value. For another example, taking the attribute information format of the current point as an example in RGB format, assuming that the first component is a G component, the second component can be an R component, and the third component can be a B component. If the first identified If the value is the first value, the decoder determines that the attribute quantization residual value of the G component is zero, and based on the second identifier obtained by decoding the code stream, obtains the attribute residual value of the R component and the attribute residual value of the B component. difference.

In this embodiment, the code stream includes the first identifier and the second identifier, the first identifier can be used to determine whether the attribute quantization residual value of the first component is zero, and the second identifier can be used to determine whether the second The property of the component quantifies whether the residual value is zero. If the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are both zero, then for the attribute quantization residual value of the first component, the attribute quantization residual value of the second component and For the attribute quantized residual value of the third component, the code stream only includes a result obtained by encoding the attribute quantized residual value of the third component.

Of course, in other alternative embodiments, if the value of the first identifier is the first value, then the attribute quantization residual value of the first component is zero, and at this time, the decoder can also sequentially obtain The attribute quantized residual value of the second component and the attribute quantized residual value of the third component are acquired. In other words, the code stream may not include the second identifier, and the code stream includes the result obtained by sequentially encoding the attribute quantization residual value of the second component and the attribute quantization residual value of the third component. This is not specifically limited.

In some embodiments, if the value of the second identifier is the first value, it is determined that the attribute quantization residual value of the second component is zero, and the attribute quantization residual value of the third component is obtained from the code stream. A difference value; if the value of the second identifier is a second value, sequentially acquire the attribute quantization residual value of the second component and the attribute quantization residual value of the third component from the code stream. For example, the first value may be 0 or other values. For example, the second value may be 1 or other values.

For example, taking the attribute information format of the current point as an example in YUV format, assuming that the first component is a U component, the second component can be a Y component, and the third component can be a V component. value is the first value, the decoder determines that the attribute quantization residual value of the Y component is zero, and obtains the attribute quantization residual value of the V component from the code stream; if the value of the second identifier is the second value , the attribute quantization residual value of the Y component and the attribute quantization residual value of the V component are sequentially obtained from the code stream. For another example, taking the attribute information format of the current point as an example in RGB format, assuming that the first component is a G component, the second component can be an R component, and the third component can be a B component. If the second identified If the value is the first value, the decoder determines that the attribute quantization residual value of the R component is zero, and obtains the attribute quantization residual value of the B component from the code stream; if the value of the second identifier is the second value, the attribute quantization residual value of the R component and the attribute quantization residual value of the B component are sequentially obtained from the code stream.

In some embodiments, the value of the first identifier is a second value; the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the third The attributes of the components quantize the residual values. For example, the second value may be 1 or other values.

For example, taking the attribute information format of the current point as an example in YUV format, if the value of the first identifier is the second value, assuming that the first component is a U component, the second component may be a Y component, and the third The component may be a V component, and the decoder may sequentially obtain the attribute quantization residual value of the U component, the attribute quantization residual value of the Y component, and the attribute quantization residual value of the V component from the code stream. For another example, taking the attribute information format of the current point as an example in RGB format, assuming that the first component is a G component, the second component can be an R component, and the third component can be a B component. If the first identified If the value is the second value, the decoder can sequentially obtain the attribute quantization residual value of the G component, the attribute quantization residual value of the R component, and the attribute quantization residual value of the B component from the code stream.

In this embodiment, the first component to be decoded at the current point (that is, the first component) is designed as a U component, a V component, a G component or a B component, which can increase the value of the first flag to the second value. The probability is equivalent to that the decoding end does not need to decode the second identifier, and furthermore, the decoding efficiency of the decoder can be improved.

In some embodiments, the S120 may include:

For each of the first component, the second component, and the third component, dequantize the attribute quantization residual value of each component to obtain the attribute residual reconstruction value of each component; obtain The attribute residual reconstruction value of each component; obtain the attribute prediction value of each component; obtain the cross-component prediction value of each component; reconstruct the attribute residual value of each component, the attribute of each component The predicted value, and the sum of the cross-component predicted values for each component, is determined as the property reconstruction value for each component.

For example, taking the attribute information format of the current point as an example in the YUV format, assuming that the first component is a U component, the second component may be a Y component, and the third component may be a V component, and the decoder obtains the first component After the attribute quantized residual value of the second component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component, the predicted attribute value of the Y component, the predicted attribute value of the U component, and the predicted attribute value of the V component can be sequentially obtained. attribute prediction value, and sequentially obtain the cross-component prediction value of the Y component, the cross-component prediction value of the U component, and the cross-component prediction value of the V component; then, the decoder converts the attribute residual value of the Y component, the attribute prediction value of the Y component And the sum of the cross-component prediction values of the Y component is determined as the attribute reconstruction value of the Y component, and the sum of the attribute residual value of the U component, the attribute prediction value of the U component, and the cross-component prediction value of the U component is determined as the U component The attribute reconstruction value of the V component, the sum of the attribute residual value of the V component, the attribute prediction value of the V component, and the cross-component prediction value of the V component is determined as the attribute reconstruction value of the V component.

For another example, taking the attribute information format of the current point as an example in RGB format, assuming that the first component is a G component, the second component may be an R component, and the third component may be a B component, and the decoder obtains the first After the attribute quantization residual value of the component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component, the attribute prediction value of the R component, the attribute prediction value of the G component, and the B component can be sequentially obtained The attribute prediction value of the R component, and sequentially obtain the cross-component prediction value of the R component, the cross-component prediction value of the G component, and the cross-component prediction value of the B component; The sum of the value and the cross-component prediction value of the R component is determined as the attribute reconstruction value of the R component, and the sum of the attribute residual value of the G component, the attribute prediction value of the G component, and the cross-component prediction value of the G component is determined as G For the attribute reconstruction value of the component, the sum of the attribute residual value of the B component, the attribute prediction value of the B component, and the cross-component prediction value of the B component is determined as the attribute reconstruction value of the B component.

It should be understood that the order in which the decoder obtains the attribute prediction values of each component of the current point may be consistent with the order in which the decoder obtains the attribute quantization residual values of each component of the current point, or may be inconsistent, and this application does not specifically limit this .

In some embodiments, the cross-component predicted value of the first component is zero; the cross-component predicted value of the first component is zero; the cross-component predicted value of the second component is the attribute residual reconstruction value of the first component ; The cross-component prediction value of the third component is the sum of the attribute residual reconstruction value of the first component and the attribute residual reconstruction value of the second component.

For example, taking the attribute information format of the current point as YUV format as an example, assuming that the first component is the U component, the second component can be the Y component, the third component can be the V component, and the cross-component prediction value of the U component is zero; the cross-component predicted value of the Y component is the attribute residual reconstruction value of the U component, and the cross-component predicted value of the V component is the sum of the attribute residual reconstruction value of the U component and the attribute residual reconstruction value of the Y component. As another example, taking the attribute information format of the current point as an example in RGB format, assuming that the first component is the G component, the second component can be the R component, and the third component can be the B component. Cross-component prediction of the G component The value is zero; the cross-component prediction value of the R component is the attribute residual reconstruction value of the G component; the cross-component prediction value of the B component is the sum of the attribute residual reconstruction value of the G component and the attribute residual reconstruction value of the R component.

In some embodiments, first, the decoder can search for N prediction points for the current point within the range formed by the points that have been decoded before the current point; Calculate the weight value corresponding to the N prediction points; finally, the decoder can obtain the attribute of each component based on the weight value corresponding to the N prediction points and the attribute reconstruction value of the N prediction points Predictive value.

For example, taking the attribute information format of the current point as YUV format as an example, after the decoder obtains the weight values corresponding to the N prediction points, it can The attribute reconstruction value of the point before the point is obtained to obtain the attribute prediction value of the Y component of the point, and based on the weight value corresponding to the N prediction points and the attribute reconstruction value of the U component of the N prediction points, the U of the point before the point is obtained The attribute prediction value of the component, based on the weight values corresponding to the N prediction points and the attribute reconstruction value of the V component of the N prediction points, the attribute prediction value of the V component of the point before the point is obtained. For another example, taking the attribute information format of the current point as an example in RGB format, after the decoder obtains the weight values corresponding to the N prediction points, it can base on the weight values corresponding to the N prediction points and the R values of the N prediction points. The attribute reconstruction value of the component, obtain the attribute prediction value of the R component of the point before the point, based on the weight value corresponding to the N prediction points and the attribute reconstruction value of the G component of the N prediction points, obtain the point before the point The attribute prediction value of the G component is based on the weight values corresponding to the N prediction points and the attribute reconstruction values of the B components of the N prediction points, and the attribute prediction value of the B component of the point before the point is obtained.

The specific execution steps of the decoding end are exemplarily described below in conjunction with specific embodiments.

Example 1:

In this embodiment, the decoding end sequentially decodes the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component of the current point from the code stream of the current point cloud. As an example, the first component is a U component, the second component may be a Y component, and the third component may be a V component. As another example, the first component is a G component, the second component may be an R component, and the third component may be a B component.

Exemplarily, the execution process at the decoding end may include the following steps:

c) Decoding and obtaining attribute quantization residual values of each component at the current point from the code stream in the order of U component, Y component, and V component (or G component, R component, and B component).

For example, if the format of the color information of the current point is YUV format, the decoder decodes the attribute quantization residual value of each component of the current point from the code stream in the order of U component, Y component, and V component. For another example, if the format of the color information of the current point is RGB format, the encoder decodes the attribute quantization residual value of each component of the current point from the code stream in the order of G component, R component, and B component.

Exemplarily, the specific execution steps include:

1) Obtain the flag bit flagu_g by decoding from the code stream. If flagu_g is 0, the attribute quantization residual value of the U component (or G component) is 0. If flagu_g is 1, the attribute of the U component (or G component) The quantized residual value is not 0.

For example, if the format of the color information of the current point is YUV format, the decoder decodes and obtains the flag bit flagu_g from the code stream. If flagu_g is 0, the attribute quantization residual value of the U component is 0, and flag_g is 1, then U The attribute quantization residual value of the component is not 0. For another example, if the color information format of the current point is in RGB format, the decoder decodes and obtains the flag bit flagu_g from the code stream. If flagu_g is 0, the attribute quantization residual value of the G component is 0. If flag_g is 1, Then the attribute quantization residual value of the G component is not 0.

2) Judging whether the attribute quantization residual value of the U component (or G component) is 0, if it is 0, perform 3), otherwise perform 4).

3) Obtain the flag bit flaguy_gr from code stream decoding, if flaguy_gr is 0, then the attribute quantization residual value of Y component (or R component) is 0, and decode and obtain V component (or B component) from the code stream Attribute quantized residual value; otherwise, sequentially decode and obtain the attribute quantized residual value of Y component, V component (or R component, B component) from the code stream.

For example, if the format of the color information of the current point is YUV format, the decoder decodes and obtains the flag bit flaguy_gr from the code stream, and if flaguy_gr is 0, the attribute quantization residual value of the Y component is 0, and decodes it from the code stream Obtain the attribute quantization residual value of the V component; otherwise, sequentially decode and obtain the attribute quantization residual value of the Y component and the attribute quantization residual value of the V component from the code stream. For another example, if the format of the color information of the current point is RGB format, the decoder decodes and obtains the flag bit flaguy_gr from the code stream. If flaguy_gr is 0, the attribute quantization residual value of the R component is 0, and the Decode to obtain the attribute quantization residual value of the B component; otherwise, decode and obtain the attribute quantization residual value of the R component and the attribute quantization residual value of the B component from the code stream in sequence.

4) Decoding in sequence from the code stream to obtain attribute quantization residual values of the U component, the Y component, and the V component (or G component, R component, and B component).

For example, if the format of the color information of the current point is YUV format, the decoder decodes and obtains the flag bit flagu_g from the code stream. If flag_g is 1, the decoder sequentially decodes and obtains the attribute quantization residual value of the U component from the code stream , the attribute quantized residual value of the Y component, and the attribute quantized residual value of the V component. For another example, if the format of the color information of the current point is in RGB format, the decoder decodes the bit flag flag_g from the code stream, and if flagu_g is 1, the decoder decodes the attribute quantization residual of the G component sequentially from the code stream value, the attribute quantized residual value of the R component, and the attribute quantized residual value of the B component.

in,

In the above scheme, if the format of the color information of the current point is YUV format, the encoder encodes the attribute quantization residual value of each component of the current point in the order of U component, Y component, and V component. If the color information of the current point The format of the information is RGB format, and the encoder encodes the attribute quantization residual value of each component in the order of G component, R component, and B component; correspondingly, if the format of the color information of the current point is YUV format, the decoder follows The order of U component, Y component, and V component decodes the attribute quantization residual value of each component of the current point. If the format of the color information of the current point is RGB format, the decoder follows the order of G component, R component, and B component. The attribute quantized residual values of the respective components are decoded.

The preferred embodiments of the present application have been described in detail above in conjunction with the accompanying drawings. However, the present application is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present application, various simple modifications can be made to the technical solutions of the present application. These simple modifications all belong to the protection scope of the present application. For example, the various specific technical features described in the above specific implementation manners can be combined in any suitable manner if there is no contradiction. Separately. As another example, any combination of various implementations of the present application can also be made, as long as they do not violate the idea of the present application, they should also be regarded as the content disclosed in the present application. It should also be understood that, in various method embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the order of execution, and the order of execution of the processes should be determined by their functions and internal logic, and should not be used in this application. The implementation of the examples constitutes no limitation.

FIG. 13 is a schematic flowchart of an encoding-based method 200 provided by an embodiment of the present application. The method 200 can be executed by an encoder or an encoding framework, such as the encoding framework shown in FIG. 4 .

As shown in Figure 13, the encoding method 200 may include:

S210, determine the attribute quantization residual value of the first component of the current point to be encoded in the current point cloud, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component; wherein, the first component is U component, V component, G component or B component;

S220. Encode the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component in sequence to obtain a code stream of the current point cloud.

In some embodiments, the code stream includes a result obtained by encoding the value of the first identifier, and the value of the first identifier is used to indicate whether the attribute quantization residual value of the first component is zero.

In some embodiments, if the value of the first flag is the first value, it means that the attribute quantization residual value of the first component is zero; if the value of the first flag is the second value, it means that the The attribute quantization residual value of the first component is not zero.

In some embodiments, if the attribute quantization residual value of the first component is zero, the code stream further includes the result obtained by encoding the value of the second identifier, and the value of the second identifier is used to represent the Whether the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are both zero.

In some embodiments, if the value of the second flag is the first value, it means that the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are both zero; if the second If the value of the flag is the second value, it means that the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are not both zero.

In some embodiments, if both the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are zero, the code stream further includes encoding the attribute quantization residual value of the third component The results obtained.

In some embodiments, if the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are not both zero, the code stream further includes the attribute quantization residual value of the second component in turn The result obtained by encoding with the attribute quantization residual value of the third component.

In some embodiments, if the attribute quantization residual value of the first component is not zero, the code stream further includes the attribute quantization residual value of the first component, the attribute quantization residual value of the second component in sequence And the result obtained by encoding the attribute quantization residual value of the third component.

In some embodiments, the method 200 may also include:

For each of the first component, the second component, and the third component, perform inverse quantization processing on the attribute quantization residual value of each component to obtain the attribute residual reconstruction value of each component;

Get the attribute residual reconstruction value of each component;

Obtain the attribute prediction value of each component;

Obtain the cross-component prediction value of each component;

The sum of the attribute residual reconstruction value of each component, the attribute prediction value of each component, and the cross-component prediction value of each component is determined as the attribute reconstruction value of each component.

In some embodiments, the cross-component predictive value of the first component is zero; the cross-component predictive value of the second component is the attribute residual reconstruction value of the first component; the cross-component predictive value of the third component is the The sum of the reconstructed attribute residual value of the first component and the reconstructed attribute residual value of the second component.

In some embodiments, N prediction points are searched for the current point within the range formed by the points encoded before the current point; according to the geometric distance between the N prediction points and the current point, the N prediction points are calculated. The weight value corresponding to the prediction point; based on the weight value corresponding to the N prediction points and the attribute reconstruction value of the N prediction points, the attribute prediction value of each component is obtained.

The specific execution steps of the encoding end will be illustrated below in combination with specific embodiments.

Example 2:

In this embodiment, the encoder sequentially encodes the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component to obtain the code of the current point cloud Stream; as an example, the first component is a U component, the second component may be a Y component, and the third component may be a V component. As another example, the first component is a G component, the second component may be an R component, and the third component may be a B component.

In this embodiment, the execution process at the encoding end may include the following steps:

delta = currValue-predictor-residualPrevComponent;

Among them, delta represents the attribute residual value of each component, currValue represents the original value or real value of each component, predictor represents the attribute prediction value of each component, and residualPrevComponent represents the cross-component prediction value of each component. For example, if the format of the color information of the current point is YUV format, each component can include Y component, U component and V component; if the format of the color information of the current point is RGB format, each component can include R component, G component and the B component.

Exemplarily, for the Y component and the R component, since they are the first encoded components, the cross-component prediction value of the Y component and the R component can be set to 0, and for the U component, V component, G component, and B component, its The cross-component predictive value is determined according to the attribute residual value obtained through inverse quantization of the attribute quantization residual value of the previously encoded component. For example, the cross-component prediction value of the U component can be the attribute residual reconstruction value obtained by inverse quantization of the attribute quantization residual value of the Y component, and the cross-component prediction value of the G component can be the attribute quantization residual value of the R component. The reconstructed value of the attribute residual obtained by inverse quantization. For another example, the cross-component prediction value of the V component may be the attribute residual reconstruction value obtained by dequantizing the attribute quantization residual value of the Y component and the attribute residual reconstruction value obtained by dequantizing the attribute quantization residual value of the U component. The sum of values, the cross-component prediction value of the B component can be the attribute residual value obtained by dequantizing the attribute quantized residual reconstruction value of the R component and the attribute residual obtained by dequantizing the attribute quantized residual value of the G component Sum of reconstructed values.

For example, if the format of the color information of the current point is YUV format, entropy encoding is performed on the attribute quantization residual value of each component in the order of U component, Y component, and V component to obtain the code stream of the point cloud. For another example, if the format of the color information of the current point is RGB format, entropy encoding is performed on the attribute quantization residual value of each component in the order of G component, R component, and B component to obtain the code stream of the point cloud.

1) On the one hand, introduce a flag bit flag_g, which can be used to indicate whether the attribute quantization residual value of the U component is 0 for points whose attribute information format is YUV format, and for points whose attribute information format is RGB format, It can be used to indicate whether the attribute quantization residual value of the G component is 0. For example, if the attribute quantization residual value of the U component (or G component) is 0, then flagu_g=0, otherwise flagu_g=1, the encoder encodes the value of flag_g and writes it into the code stream. On the other hand, another flag bit flaguy_gr is introduced, which can be used to indicate whether the attribute residual quantization value of the U component and the attribute residual quantization value of the Y component are both 0 for points whose attribute information format is YUV format. The format of the information is a point in RGB format, which can be used to indicate whether the attribute residual quantization value of the G component and the attribute residual quantization value of the R component are both 0. For example, if both the attribute residual quantization value of the U component and the attribute residual quantization value of the Y component are 0, then flaguy_gr=0, otherwise flaguy_gr=1. For another example, if both the attribute residual quantization value of the G component and the attribute residual quantization value of the R component are 0, then flaguy_gr=0, otherwise flaguy_gr=1.

2) The encoder judges whether the attribute quantization residual value of the U component (or G component) is 0, and if it is 0, executes the following 3), otherwise executes the following 4).

3), the encoder encodes the value of flaguy_gr, and judges whether the attribute quantization residual value of the Y component (or R component) is 0, if the attribute quantization residual value of the Y component (or R component) is 0, then The attribute quantization residual value of the V component (or B component) is encoded, otherwise, the attribute residual quantization values of the Y component and the V component (or R component and B component) are encoded sequentially.

For example, if the format of the color information of the current point is YUV format, the encoder encodes the value of flaguy_gr, and judges whether the attribute quantization residual value of the Y component is 0, if the attribute quantization residual value of the Y component is 0 , then encode the attribute quantized residual value of the V component, otherwise encode the attribute residual quantized value of the Y component and the attribute residual quantized value of the V component in sequence. For another example, if the color information format of the current point is in RGB format, the encoder encodes the value of flaguy_gr and judges whether the attribute quantization residual value of the R component is 0. If the attribute quantization residual value of the R component is 0, the attribute quantization residual value of the B component is encoded, otherwise, the attribute residual quantization value of the R component and the attribute residual quantization value of the B component are encoded sequentially.

4) The encoder sequentially encodes the attribute quantized residual values of the U component, the Y component, and the V component (or G component, R component, and B component).

For example, if the format of the color information of the current point is YUV format, the encoder sequentially encodes the attribute quantization residual value of the U component, the attribute quantization residual value of the Y component, and the attribute quantization residual value of the V component. For another example, if the color information of the current point is in the RGB format, the encoder sequentially encodes the attribute quantization residual value of the G component, the attribute quantization residual value of the R component, and the attribute quantization residual value of the B component.

in,

The encoder or decoder provided by the embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 14 is a schematic block diagram of a decoder 300 provided by an embodiment of the present application.

As shown in Figure 14, the decoder 300 may include:

The decoding unit 310 is used to sequentially decode the attribute quantized residual value of the first component of the current point, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component from the code stream of the current point cloud; wherein , the first component is a U component, a V component, a G component or a B component;

The acquiring unit 320 is configured to acquire the attribute reconstruction value of the current point based on the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component.

In some embodiments, the decoding unit 310 is specifically used for:

In some embodiments, the value of the first identifier is a first value; wherein, the decoding unit 310 is specifically configured to:

determining that the attribute quantization residual value of the first component is zero;

Based on the second identifier obtained by decoding the code stream, obtain the attribute residual value of the second component and the attribute residual value of the third component; the value of the second identifier is used to represent the attribute of the first component Whether the quantized residual value and the attribute quantized residual value of the second component are both zero.

In some embodiments, the decoding unit 310 is specifically used for:

If the value of the second identifier is the first value, determine that the attribute quantization residual value of the second component is zero, and acquire the attribute quantization residual value of the third component from the code stream;

If the value of the second identifier is the second value, the attribute quantization residual value of the second component and the attribute quantization residual value of the third component are sequentially obtained from the code stream.

In some embodiments, the value of the first identifier is a second value; wherein, the decoding unit 310 is specifically configured to:

The attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component are sequentially acquired from the code stream.

In some embodiments, the acquiring unit 320 is specifically configured to:

Get the attribute residual reconstruction value of each component;

Obtain the attribute prediction value of each component;

Obtain the cross-component prediction value of each component;

In some embodiments, the acquiring unit 320 is specifically configured to:

Find N predicted points for the current point within the range formed by the points that have been decoded before the current point;

Calculating weight values corresponding to the N predicted points according to the geometric distance between the N predicted points and the current point;

Based on the weight values corresponding to the N prediction points and the attribute reconstruction values of the N prediction points, the attribute prediction value of each component is obtained.

It should be noted that the decoder 300 can also be combined with the decoding framework shown in FIG. 5 , that is, units in the decoder 300 can be replaced or combined with relevant parts in the decoding framework. For example, the acquiring unit 320 can be used to implement the attribute prediction part in the decoding framework.

FIG. 15 is a schematic block diagram of an encoder 400 provided by an embodiment of the present application.

As shown in Figure 15, the encoder 400 may include:

A determination unit 410, configured to determine the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component of the current point to be encoded in the current point cloud; wherein, the The first component is a U component, a V component, a G component or a B component;

An encoding unit 420, configured to sequentially encode the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component to obtain the code stream of the current point cloud .

In some embodiments, the determining unit 410 is also used to:

Get the attribute residual reconstruction value of each component;

Obtain the attribute prediction value of each component;

Obtain the cross-component prediction value of each component;

In some embodiments, the determining unit 410 is specifically configured to:

Find N predicted points for the current point within the range formed by the encoded points before the current point;

It should be noted that the encoder 400 can also be combined with the encoding framework shown in FIG. 4 , that is, units in the encoder 400 can be replaced or combined with relevant parts in the encoding framework. For example, the determining unit 410 can be used to implement the attribute prediction part in the encoding framework.

It should be understood that the device embodiment and the method embodiment may correspond to each other, and similar descriptions may refer to the method embodiment. To avoid repetition, details are not repeated here. Specifically, the decoder 300 may correspond to the corresponding subject in the method 100 of the embodiment of the present application, and each unit in the decoder 300 is to realize the corresponding process in the method 100, similarly, the encoder 400 may correspond to the execution The corresponding subjects in the method 200 in the embodiment of the present application, and each unit in the encoder 400 are to implement the corresponding processes in the method 200 respectively, and for the sake of brevity, details are not repeated here.

It should also be understood that the various units in the decoder 300 or the encoder 400 involved in the embodiment of the present application can be respectively or all combined into one or several other units to form, or some (some) units can be further disassembled. Divided into a plurality of functionally smaller units, this can achieve the same operation without affecting the realization of the technical effects of the embodiments of the present application. The above-mentioned units are divided based on logical functions. In practical applications, the functions of one unit may also be realized by multiple units, or the functions of multiple units may be realized by one unit. In other embodiments of the present application, the decoder 300 or the encoder 400 may also include other units. In practical applications, these functions may also be implemented with the assistance of other units, and may be implemented cooperatively by multiple units. According to another embodiment of the present application, a general-purpose computing device including a general-purpose computer such as a central processing unit (CPU), a random access storage medium (RAM), a read-only storage medium (ROM) and a storage element Run a computer program (including program code) capable of executing the steps involved in the corresponding method to construct the decoder 300 or encoder 400 involved in the embodiment of the present application, and realize the point cloud attribute prediction based on the embodiment of the present application Codec method. The computer program can be recorded in, for example, a computer-readable storage medium, and loaded on any electronic device with data processing capability through the computer-readable storage medium, and run in it to implement the corresponding method of the embodiment of the present application.

In other words, the units mentioned above can be implemented in the form of hardware, can also be implemented by instructions in the form of software, and can also be implemented in the form of a combination of software and hardware. Specifically, each step of the method embodiment in the embodiment of the present application can be completed by an integrated logic circuit of the hardware in the processor and/or instructions in the form of software, and the steps of the method disclosed in the embodiment of the present application can be directly embodied as hardware The execution of the decoding processor is completed, or the combination of hardware and software in the decoding processor is used to complete the execution. Optionally, the software may be located in mature storage media in the field such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, and registers. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps in the above method embodiments in combination with its hardware.

FIG. 16 is a schematic structural diagram of a codec device 500 provided by an embodiment of the present application.

As shown in FIG. 16 , the codec device 500 includes at least a processor 510 and a computer-readable storage medium 520 . Wherein, the processor 510 and the computer-readable storage medium 520 may be connected through a bus or in other ways. The computer-readable storage medium 520 is used for storing a computer program 521 , and the computer program 521 includes computer instructions, and the processor 510 is used for executing the computer instructions stored in the computer-readable storage medium 520 . The processor 510 is the computing core and the control core of the codec device 500, which is suitable for realizing one or more computer instructions, and is specifically suitable for loading and executing one or more computer instructions so as to realize corresponding method procedures or corresponding functions.

As an example, the processor 510 may also be called a central processing unit (Central Processing Unit, CPU). The processor 510 may include but not limited to: a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) Or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

As an example, the computer-readable storage medium 520 can be a high-speed RAM memory, or a non-volatile memory (Non-VolatileMemory), such as at least one disk memory; computer readable storage medium. Specifically, the computer-readable storage medium 520 includes, but is not limited to: volatile memory and/or non-volatile memory. Among them, the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electronically programmable Erase Programmable Read-Only Memory (Electrically EPROM, EEPROM) or Flash. The volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (Static RAM, SRAM), Dynamic Random Access Memory (Dynamic RAM, DRAM), Synchronous Dynamic Random Access Memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous connection dynamic random access memory (synch link DRAM, SLDRAM) and Direct Memory Bus Random Access Memory (Direct Rambus RAM, DR RAM).

In one implementation, the codec device 500 may be the encoding framework shown in FIG. 4 or the encoder 400 shown in FIG. 15; the first computer instruction is stored in the computer-readable storage medium 520; the processor 510 Load and execute the first computer instruction stored in the computer-readable storage medium 520, to realize the corresponding steps in the method embodiment shown in FIG. 13; Step 510 loads and executes corresponding steps, which will not be repeated here to avoid repetition. In one implementation, the codec device 500 may be the decoding framework shown in FIG. 5 or the decoder 300 shown in FIG. 14 ; second computer instructions are stored in the computer-readable storage medium 520 ; Load and execute the second computer instructions stored in the computer-readable storage medium 520 to implement the corresponding steps in the method embodiment shown in FIG. 12; Step 510 loads and executes corresponding steps, which will not be repeated here to avoid repetition.

According to another aspect of the present application, the embodiment of the present application further provides a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in the codec device 500 and is used to store programs and data. For example, computer readable storage medium 520 . It can be understood that the computer-readable storage medium 520 here may include a built-in storage medium in the codec device 500 , and of course may also include an extended storage medium supported by the codec device 500 . The computer-readable storage medium provides a storage space, and the storage space stores the operating system of the codec device 500 . Moreover, one or more computer instructions adapted to be loaded and executed by the processor 510 are also stored in the storage space, and these computer instructions may be one or more computer programs 521 (including program codes). These computer instructions are used for the computer to execute the coding and decoding methods based on point cloud attribute prediction provided in the various optional ways above.

According to another aspect of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. For example, computer program 521 . At this point, the codec device 500 may be a computer, the processor 510 reads the computer instructions from the computer-readable storage medium 520, and the processor 510 executes the computer instructions, so that the computer executes the point-based Encoding and decoding methods for cloud property prediction.

In other words, when implemented using software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the procedures of the embodiments of the present application are run in whole or in part or the functions of the embodiments of the present application are realized. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable device. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, from a website, computer, server, or data center via Wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) transmission to another website site, computer, server or data center.

Those skilled in the art can appreciate that the units and process steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

Finally, it should be noted that the above content is only a specific embodiment of the application, but the scope of protection of the application is not limited thereto. Anyone familiar with the technical field can easily think of Any changes or substitutions shall fall within the scope of protection of this application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

A decoding method, characterized in that, comprising:

Decoding the attribute quantized residual value of the first component of the current point, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component from the code stream of the current point cloud in sequence; wherein, the first component It is U component, V component, G component or B component;

Acquiring an attribute reconstruction value of the current point based on the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component.
The method according to claim 1, wherein the attribute quantization residual value of the first component of the current point, the attribute quantization residual value of the second component, and the third component are sequentially decoded from the code stream of the current point cloud The properties of the components quantify the residual values, including:

Decoding the code stream to obtain a first identifier, the value of the first identifier is used to indicate whether the attribute quantization residual value of the first component is zero;

Analyze the code stream based on the value of the first identifier, and obtain the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization value of the third component residual value.
The method according to claim 2, wherein the value of the first identifier is a first value;

Wherein, the code stream is analyzed based on the value of the first identifier, and the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the third The properties of the components quantify the residual values, including:

determining that the attribute quantization residual value of the first component is zero;

Based on the second identifier obtained by decoding the code stream, the attribute residual value of the second component and the attribute residual value of the third component are obtained; the value of the second identifier is used to represent the Whether the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are both zero.
The method according to claim 3, wherein the attribute residual value of the second component and the attribute residual value of the third component are obtained based on the second identifier obtained by decoding the code stream values, including:

If the value of the second identifier is the first value, determine that the attribute quantization residual value of the second component is zero, and obtain the attribute quantization residual value of the third component from the code stream value;

If the value of the second identifier is a second value, sequentially acquire the attribute quantization residual value of the second component and the attribute quantization residual value of the third component from the code stream.
The method according to claim 2, wherein the value of the first identifier is a second value;

Wherein, the code stream is analyzed based on the value of the first identifier, and the attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the third The properties of the components quantify the residual values, including:

The attribute quantization residual value of the first component, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component are sequentially acquired from the code stream.
The method according to any one of claims 1 to 5, wherein the attribute quantization residual value based on the first component, the attribute quantization residual value of the second component, and the third The attribute quantization residual value of the component is used to obtain the attribute reconstruction value of the current point, including:

For each of the first component, the second component, and the third component, dequantize the attribute quantization residual value of each component to obtain the attribute residual value of each component rebuild value;

Obtain the attribute residual reconstruction value of each component;

Obtaining the attribute prediction value of each component;

obtaining cross-component predictors for each of the components;

A sum of the attribute residual reconstruction value of each component, the attribute prediction value of each component, and the cross-component prediction value of each component is determined as the attribute reconstruction value of each component.
The method according to claim 6, wherein the cross-component predictive value of the first component is zero; the cross-component predictive value of the second component is the attribute residual reconstruction value of the first component; The cross-component prediction value of the third component is the sum of the attribute residual reconstruction value of the first component and the attribute residual reconstruction value of the second component.
The method according to claim 6, wherein said obtaining the attribute prediction value of each component comprises:

Searching for N prediction points for the current point within the range formed by the points that have been decoded before the current point;

calculating weight values corresponding to the N predicted points according to the geometric distance between the N predicted points and the current point;

Based on the weight values corresponding to the N prediction points and the attribute reconstruction values of the N prediction points, the attribute prediction value of each component is acquired.
A coding method, characterized in that, comprising:

Determine the attribute quantization residual value of the first component of the current point to be encoded in the current point cloud, the attribute quantization residual value of the second component and the attribute quantization residual value of the third component; wherein, the first component is U Component, V component, G component or B component;

The attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component are sequentially encoded to obtain the code stream of the current point cloud.
The method according to claim 9, wherein the code stream includes the result obtained by encoding the value of the first identification, and the value of the first identification is used to represent the attribute quantization of the first component Whether the residual value is zero.
The method according to claim 10, wherein if the value of the first flag is a first value, it means that the attribute quantization residual value of the first component is zero; if the value of the first flag is If the value is the second value, it means that the attribute quantization residual value of the first component is not zero.
The method according to claim 10 or 11, wherein if the attribute quantization residual value of the first component is zero, the code stream further includes the result obtained by encoding the value of the second identifier, The value of the second flag is used to indicate whether the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are both zero.
The method according to claim 12, wherein if the value of the second flag is a first value, it indicates that the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are The differences are all zero; if the value of the second identifier is a second value, it means that the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are not both zero.
The method according to claim 12, wherein if the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are both zero, the code stream further includes The attribute quantization residual value of the third component is the result obtained by encoding.
The method according to claim 12, wherein if the attribute quantization residual value of the first component and the attribute quantization residual value of the second component are not all zero, the code stream further includes sequentially A result obtained by encoding the attribute quantized residual value of the second component and the attribute quantized residual value of the third component.
The method according to claim 10 or 11, wherein if the attribute quantization residual value of the first component is not zero, the code stream further includes sequentially quantizing the attribute quantization residual of the first component value, the attribute quantization residual value of the second component, and the attribute quantization residual value of the third component are encoded results.
The method according to any one of claims 9 to 16, further comprising:

For each of the first component, the second component, and the third component, dequantize the attribute quantization residual value of each component to obtain the attribute residual value of each component rebuild value;

Obtain the attribute residual reconstruction value of each component;

Obtaining the attribute prediction value of each component;

obtaining cross-component predictors for each of the components;

A sum of the attribute residual reconstruction value of each component, the attribute prediction value of each component, and the cross-component prediction value of each component is determined as the attribute reconstruction value of each component.
The method according to claim 17, wherein the cross-component predictive value of the first component is zero; the cross-component predictive value of the second component is the attribute residual reconstruction value of the first component; The cross-component prediction value of the third component is the sum of the attribute residual reconstruction value of the first component and the attribute residual reconstruction value of the second component.
The method according to claim 17, wherein said obtaining the attribute prediction value of each component comprises:

Searching for N predicted points for the current point within the range formed by the encoded points before the current point;

calculating weight values corresponding to the N predicted points according to the geometric distance between the N predicted points and the current point;

Based on the weight values corresponding to the N prediction points and the attribute reconstruction values of the N prediction points, the attribute prediction value of each component is acquired.
A decoder, characterized in that it comprises:

The decoding unit is used to sequentially decode the attribute quantized residual value of the first component of the current point, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component from the code stream of the current point cloud; wherein, The first component is a U component, a V component, a G component or a B component;

An acquiring unit, configured to acquire the attribute reconstruction of the current point based on the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component value.
An encoder, characterized in that it comprises:

The determination unit is used to determine the attribute quantization residual value of the first component, the attribute quantization residual value of the second component and the attribute quantization residual value of the third component of the current point to be encoded in the current point cloud; wherein, the The first component is a U component, a V component, a G component or a B component;

An encoding unit, configured to sequentially encode the attribute quantized residual value of the first component, the attribute quantized residual value of the second component, and the attribute quantized residual value of the third component to obtain the current point cloud stream.
A decoding device, characterized in that it comprises:

a processor adapted to execute a computer program;

A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the decoding method according to any one of claims 1 to 8 is implemented.
An encoding device, characterized in that it comprises:

a processor adapted to execute a computer program;

A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the encoding method according to any one of claims 9 to 19 is realized.
A computer-readable storage medium, characterized by being used for storing a computer program, the computer program causes a computer to execute the decoding method according to any one of claims 1 to 8.
A computer-readable storage medium is characterized in that it is used to store a computer program, the computer program causes a computer to execute the encoding method according to any one of claims 9 to 19.